code: def load_editing_model():
      if not settings.ENABLE_EDITOR_MODEL:
          return None
  
      model = T5ForTokenClassification.from_pretrained(
          settings.EDITOR_MODEL_NAME,
          torch_dtype=settings.MODEL_DTYPE,
      ).to(settings.TORCH_DEVICE_MODEL)
      model.eval()
  
      model.config.label2id = {
          "equal": 0,
          "delete": 1,
          "newline-1": 2,
          "space-1": 3,
      }
      model.config.id2label = {
          v: k for k, v in model.config.label2id.items()
      }
      return model
  
file_path: pdf-to-markdown/marker/postprocessors/editor.py
imports: from collections import defaultdict, Counter
  from itertools import chain
  from typing import Optional
  from transformers import AutoTokenizer
  from marker.settings import settings
  import torch
  import torch.nn.functional
  from marker.postprocessors.t5 import T5ForTokenClassification, byt5_tokenize
label_desc: Use image node_id 1 for calling a global function with example usage: load_editing_model() and returns: model, None